During autonomous driving of the autonomous vehicle, an environment around a vehicle body of the autonomous vehicle, particularly a driving state of other vehicles around the autonomous vehicle exerts an important influence on autonomous driving policies of the autonomous vehicle such as trajectory tracking, collision prediction and vehicle lane changes. Hence, it is of great importance to obtain the driving directions of other vehicles around the autonomous vehicle in the autonomous driving technologies of the autonomous vehicle.
In the prior art, there are mainly two methods for judging vehicle driving direction: (1) a deep learning method: judging the vehicle driving direction based on deep learning of collected big data; (2) a trajectory-tracking method: judging the vehicle driving direction based on the vehicle's driving trajectory. When the deep learning method is employed, since the collected data is incomplete, it might be impossible to accurately judge the vehicle driving direction in the case of confrontation with sudden situations; when the trajectory-tracking method is employed, judgment can be made only when the vehicle moves; if the vehicle is in a stationary state, judgement of the vehicle driving direction cannot be performed. Hence, it is desirable to provide a vehicle driving direction judging method that is capable of suiting various driving scenarios and accurately obtaining the vehicle driving direction.